Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition
Objective: Recording attendance is a critical process in academic institutions due to its significant impact on student performance and engagement. Current methods for recording attendance are often time-consuming and labour-intensive for lecturers and administrative staff, necessitating the develop...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
An-Najah National University
2025-02-01
|
| Series: | مجلة جامعة النجاح للأبحاث العلوم الطبيعية |
| Subjects: | |
| Online Access: | https://journals.najah.edu/media/journals/full_texts/14_gZanGop.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849339804306636800 |
|---|---|
| author | Ahmad S. Lateef Mohammed Y. Kamil |
| author_facet | Ahmad S. Lateef Mohammed Y. Kamil |
| author_sort | Ahmad S. Lateef |
| collection | DOAJ |
| description | Objective: Recording attendance is a critical process in academic institutions due to its significant impact on student performance and engagement. Current methods for recording attendance are often time-consuming and labour-intensive for lecturers and administrative staff, necessitating the development of more efficient and flexible solutions. While various automated attendance systems have been proposed, they often encounter challenges related to cost, implementation complexity, or reliability, hindering widespread adoption in educational settings. Method: This paper introduces a novel approach to automating attendance registration using face recognition technology. Our method integrates multiple feature extraction algorithms within a user-friendly graphical interface, specifically designed in English to enhance usability. By using existing security cameras commonly found in academic institutions, our approach addresses both cost and time inefficiencies. The attendance registration process involves capturing a video of the classroom, which is then processed to identify and log student attendance in a CSV file. A significant aspect of our study is using a comprehensive dataset comprising 2,170 images collected from 31 students at Mustansiriyah University. This extensive dataset enhances the robustness and reliability of our system, providing a diverse range of facial expressions, angles, and lighting conditions that improve the accuracy and generalizability of our model. Result: The system demonstrated accuracy of up to 100%, with deep learning algorithms outperforming machine learning methods. Conclusion: These promising results suggest that face recognition technology can effectively streamline and automate attendance tracking, offering a viable solution for educational institutions seeking to improve operational efficiency and accuracy |
| format | Article |
| id | doaj-art-d5442a6f54654dc8b313d7257eae8faa |
| institution | Kabale University |
| issn | 1727-2114 2311-8865 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | An-Najah National University |
| record_format | Article |
| series | مجلة جامعة النجاح للأبحاث العلوم الطبيعية |
| spelling | doaj-art-d5442a6f54654dc8b313d7257eae8faa2025-08-20T03:44:03ZengAn-Najah National Universityمجلة جامعة النجاح للأبحاث العلوم الطبيعية1727-21142311-88652025-02-0139221322410.35552/anujr.a.39.2.2377Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial RecognitionAhmad S. Lateef0Mohammed Y. Kamil1Mustansiriyah University, College of Science, Baghdad, IraqMustansiriyah University, College of Science, Baghdad, IraqObjective: Recording attendance is a critical process in academic institutions due to its significant impact on student performance and engagement. Current methods for recording attendance are often time-consuming and labour-intensive for lecturers and administrative staff, necessitating the development of more efficient and flexible solutions. While various automated attendance systems have been proposed, they often encounter challenges related to cost, implementation complexity, or reliability, hindering widespread adoption in educational settings. Method: This paper introduces a novel approach to automating attendance registration using face recognition technology. Our method integrates multiple feature extraction algorithms within a user-friendly graphical interface, specifically designed in English to enhance usability. By using existing security cameras commonly found in academic institutions, our approach addresses both cost and time inefficiencies. The attendance registration process involves capturing a video of the classroom, which is then processed to identify and log student attendance in a CSV file. A significant aspect of our study is using a comprehensive dataset comprising 2,170 images collected from 31 students at Mustansiriyah University. This extensive dataset enhances the robustness and reliability of our system, providing a diverse range of facial expressions, angles, and lighting conditions that improve the accuracy and generalizability of our model. Result: The system demonstrated accuracy of up to 100%, with deep learning algorithms outperforming machine learning methods. Conclusion: These promising results suggest that face recognition technology can effectively streamline and automate attendance tracking, offering a viable solution for educational institutions seeking to improve operational efficiency and accuracyhttps://journals.najah.edu/media/journals/full_texts/14_gZanGop.pdfdeep learningface recognitionmysqlattendance managementyolov7face detection |
| spellingShingle | Ahmad S. Lateef Mohammed Y. Kamil Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition مجلة جامعة النجاح للأبحاث العلوم الطبيعية deep learning face recognition mysql attendance management yolov7 face detection |
| title | Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition |
| title_full | Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition |
| title_fullStr | Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition |
| title_full_unstemmed | Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition |
| title_short | Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition |
| title_sort | effortless student attendance a smart human computer interactive system using real time facial recognition |
| topic | deep learning face recognition mysql attendance management yolov7 face detection |
| url | https://journals.najah.edu/media/journals/full_texts/14_gZanGop.pdf |
| work_keys_str_mv | AT ahmadslateef effortlessstudentattendanceasmarthumancomputerinteractivesystemusingrealtimefacialrecognition AT mohammedykamil effortlessstudentattendanceasmarthumancomputerinteractivesystemusingrealtimefacialrecognition |